Spectrum analyzers are important test instruments applicable to a wide range of technical measurements, primarily electrical and mechanical. As implied by the name, a spectrum analyzer processes an input signal to separate and measure the individual spectral components of the signal, and to order them according to their frequency.
Two types of spectrum analyzers predominate: swept analyzers and FFT (Fast Fourier Transform) analyzers. Parallel-filter analyzers, formerly popular, have largely been superceded by FFT designs. Swept analyzers operate by tuning a filter across the frequency band of interest and measuring the components passing through the filter, associating them with the instantaneous tuning frequency. The tuning action is usually repetitive in order to refresh a dynamic display of the signal components. FFT analyzers, on the other hand, are based on computation: digital data is produced by sampling and digitizing the signal, and computer-like hardware operates on a block of this data to produce information about the frequency composition of the signal.
There is a large class of signals which create analysis problems for both types of analyzers. The class includes periodic signals composed of distinct segments of time, often having distinctive waveforms within each segment. A common example of a signal having such periodic segments is a composite television waveform, such as illustrated in FIG. 1a, which shows one period (about 63 microseconds) of a TV test waveform which generates a single color bar in the center of the TV monitor. Several distinct segments are evident in the illustration: the horizontal sync pulse 2, the color reference "burst" 4, and the color bar signal 6. For such a waveform, both types of analyzers can readily measure the total spectrum of the TV signal. But often what is wanted is, instead, the spectrum of one of the segments of the waveform, such as the color burst 4. More than that, it is often desired to determine the spectrum of the underlying continuous signal, of which the color burst is but a gated sample. Since one often needs to discover certain imperfections, Such as power supply sidebands, in the underlying original signal, narrowband spectrum analysis is needed to distinguish such sidebands from the nearby carrier.
Analyzing the total spectrum of the TV signal of FIG. 1a brings confusion, since it is not at all evident which spectral components are due to the reference burst segment and which are due to the color bar segment in the video portion of the signal. In fact, because the sinusoidal frequency in both segments is the same (3.58 MHz for the U.S. television standard), and because the segments have the same periodicity, their spectral components will coincide in frequency and, therefore, they will be inseparable.
Another example from this class of signal is digital data transmitted in repetitive "frames", with a short synchronizing segment at the beginning of the frame. The spectral energy of the synchronizing segment might be negligible compared with that of the ensuing data and would be indistinguishable in a spectrum plot.
Time gating is the traditional method--used with both major types of spectrum analyzers--for eliminating spectral components due to other parts of the signal. That is, the signal to be analyzed is routed through a switch which is enabled only during the segment of interest. Time gating is intrinsic, of course, in FFT analyzers, which operate on a finite block of data. But it is an add-on feature for swept analyzers. FIG. 2 shows, in block-diagram form, how time gating may be applied to a swept analyzer. A gate generator 22 is triggered by a synchronizing signal 21. The generator is adjusted so that the time position of its control output 27 coincides with the occurrence of the desired segment of the signal. Swept spectrum analyzer 23 is shown partitioned into a heterodyne converter/intermediate frequency section 24 and a detector/display section 26. A-signal-interrupting switch 25 is placed between these sections. Control output 27 enables the switch 25, allowing only the desired signal segment to pass to the detector/display 26.
But time gating does not work well when narrowband analysis is needed. When it is used with a swept analyzer, there is a transient problem: the IF filter must settle before the switch is enabled to pass the signal. This requires a filter bandwidth somewhat greater than the inverse of the segment duration, and this bandwidth is often too wide for the desired frequency resolution. A FFT analyzer has the same problem: its resolution is limited by the inverse of the data block length, which is the time duration of the segment.
Another way of stating the issue is that separating narrowband data in a gated signal, such as the TV example above, requires coherent observation over a time comprising many gated samples, just as would be required were the signal not gated. For instance, to detect high level sidebands spaced 120 Hz from the color subcarrier would require an observation "window" at least 10 milliseconds wide, whether the subcarrier is sampled (i.e., gated) or continuous. This means processing at least 160 periods of the TV waveform. Therefore, the signal must be gated before high-resolution analysis. Prior art techniques have not incorporated this possibility.